The Holy Bible:

filtered_books_words %>%
  filter(book == "The Holy Bible") %>%
  inner_join(bing, by = "word") %>%
  count(word, sentiment, sort = TRUE) %>%
  acast(word ~ sentiment, value.var = "n", fill = 0) %>%
  comparison.cloud(colors = c("#cf0a00","#1a954d"),
                   random.order = FALSE,
                   rot.per = 0,
                   max.words = 50)

The Quran:

filtered_books_words %>%
  filter(book == "The Quran") %>%
  inner_join(bing, by = "word") %>%
  count(word, sentiment, sort = TRUE) %>%
  acast(word ~ sentiment, value.var = "n", fill = 0) %>%
  comparison.cloud(colors = c("#cf0a00","#1a954d"),
                   random.order = FALSE,
                   rot.per = 0,
                   max.words = 50)

We conclude that all Holy Books have similar odd of words expressing positive and negative sentiments. However the study performed here does not consider the context of use of these words, only their independent meaning, through the use of tokens. A more accurate study can be performed with the use of tf–idf (term frequency-inverse document frequency), which could classify better the frequency of each word and sentiment.